𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Variable Selection for Clustering with Gaussian Mixture Models

✍ Scribed by Cathy Maugis; Gilles Celeux; Marie-Laure Martin-Magniette

Book ID
109224088
Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
245 KB
Volume
65
Category
Article
ISSN
0006-341X

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Clustering with block mixture models
Clustering with block mixture models
✍ GΓ©rard Govaert; Mohamed Nadif πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 169 KB

Basing cluster analysis on mixture models has become a classical and powerful approach. Until now, this approach, which allows to explain some classic clustering criteria such as the well-known k-means criteria and to propose general criteria, has been developed to classify a set of objects measured

Tree-based clustering for gaussian mixtu
Tree-based clustering for gaussian mixture HMMs
✍ Tsuneo Kato; Shingo Kuroiwa; Tohru Shimizu; Norio Higuchi πŸ“‚ Article πŸ“… 2002 πŸ› John Wiley and Sons 🌐 English βš– 242 KB

## Abstract Tree‐based clustering is an effective method for sharing the state of an HMM in which clustering is applied to a set of context‐dependent models with the phoneme context as the splitting condition. In past papers, the method has been restricted to the single Gaussian HMM. The single Gau